Neural network approximates potential from Hamiltonian trajectories then equation discovery extracts algebraic expression matching ground truth on oscillators, central force, and Coulomb problems.
Proceedings of the National Academy of Sciences 113(15), 3932–3937 (2016)
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Learning and Interpreting Potentials for Classical Hamiltonian Systems
Neural network approximates potential from Hamiltonian trajectories then equation discovery extracts algebraic expression matching ground truth on oscillators, central force, and Coulomb problems.